Image and Video Forgery Detection
4 papers with code • 0 benchmarks • 0 datasets
Benchmarks
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Most implemented papers
Capsule-Forensics: Using Capsule Networks to Detect Forged Images and Videos
Recent advances in media generation techniques have made it easier for attackers to create forged images and videos.
Use of a Capsule Network to Detect Fake Images and Videos
In this paper, we introduce a capsule network that can detect various kinds of attacks, from presentation attacks using printed images and replayed videos to attacks using fake videos created using deep learning.
Towards Robust Tampered Text Detection in Document Image: New Dataset and New Solution
In this paper, we propose a novel framework to capture more fine-grained clues in complex scenarios for tampered text detection, termed as Document Tampering Detector (DTD), which consists of a Frequency Perception Head (FPH) to compensate the deficiencies caused by the inconspicuous visual features, and a Multi-view Iterative Decoder (MID) for fully utilizing the information of features in different scales.
AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensics
To achieve this, we propose a new approach that leverages the DALL-E2 language-image model to automatically generate and splice masked regions guided by a text prompt.